Artificial intelligence (AI) and machine learning (ML) have become essential parts of the toolset for many organizations. When used effectively, these tools provide actionable insights that drive critical decisions and enable organizations to create exciting, new, and innovative products and services. This course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, all while following a methodical workflow for developing data-driven solutions.
Learning Objectives
In this course, you will develop AI solutions for business problems. You will:
- Solve a given business problem using AI and ML
- Prepare data for use in machine learning
- Train, evaluate, and tune a machine learning model
- Build linear regression models
- Build forecasting models
- Build classification models using logistic regression and k -nearest neighbor
- Build clustering models
- Build classification and regression models using decision trees and random forests
- Build classification and regression models using support-vector machines (SVMs)
- Build artificial neural networks for deep learning
- Put machine learning models into operation using automated processes
- Maintain machine learning pipelines and models while they are in production
Framework Connections
The materials within this course focus on the NICE Framework Task, Knowledge, and Skill statements identified within the indicated NICE Framework component(s):
Competency Areas
Feedback
If you would like to provide feedback on this course, please e-mail the NICCS team at NICCS@mail.cisa.dhs.gov. Please keep in mind that NICCS does not own this course or accept payment for course entry. If you have questions related to the details of this course, such as cost, prerequisites, how to register, etc., please contact the course training provider directly. You can find course training provider contact information by following the link that says “Visit course page for more information...” on this page.